| --- |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: runs |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # runs |
|
|
| This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 3.1137 |
| - Accuracy: 0.0000 |
|
|
| ## Model description |
|
|
| More information needed |
|
|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
|
|
| The following hyperparameters were used during training: |
| - learning_rate: 0.0001 |
| - train_batch_size: 16 |
| - eval_batch_size: 48 |
| - seed: 444 |
| - gradient_accumulation_steps: 3 |
| - total_train_batch_size: 48 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: cosine_with_restarts |
| - lr_scheduler_warmup_ratio: 0.3 |
| - training_steps: 100 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | No log | 0.03 | 10 | 4.7890 | 0.1380 | |
| | 4.9326 | 0.05 | 20 | 4.4600 | 0.1310 | |
| | 4.9326 | 0.08 | 30 | 4.1364 | 0.0172 | |
| | 4.1299 | 0.11 | 40 | 3.7156 | 0.0010 | |
| | 4.1299 | 0.13 | 50 | 3.3965 | 0.0002 | |
| | 3.4428 | 0.16 | 60 | 3.2530 | 0.0002 | |
| | 3.4428 | 0.19 | 70 | 3.1727 | 0.0000 | |
| | 3.1873 | 0.21 | 80 | 3.1316 | 0.0000 | |
| | 3.1873 | 0.24 | 90 | 3.1165 | 0.0000 | |
| | 3.1176 | 0.26 | 100 | 3.1137 | 0.0000 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.37.2 |
| - Pytorch 2.2.0+cu121 |
| - Datasets 2.17.0 |
| - Tokenizers 0.15.1 |
|
|
